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Amazon EMR (Elastic MapReduce) vs. SAP Vora

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon EMR
Score 9.0 out of 10
N/A
Amazon EMR is a cloud-native big data platform for processing vast amounts of data quickly, at scale. Using open source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi (Incubating), and Presto, coupled with the scalability of Amazon EC2 and scalable storage of Amazon S3, EMR gives analytical teams the engines and elasticity to run Petabyte-scale analysis.N/A
SAP Vora
Score 6.0 out of 10
N/A
SAP Vora is a computing engine designed to provide better accessibility to Hadoop data from SAP HANA. SAP Vora manages unstructured Hadoop data by building structured data hierarchies and making the data queryable through an SQL interface.N/A
Pricing
Amazon EMR (Elastic MapReduce)SAP Vora
Editions & Modules
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Offerings
Pricing Offerings
Amazon EMRSAP Vora
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
Amazon EMR (Elastic MapReduce)SAP Vora
Considered Both Products
Amazon EMR
Verified User
Anonymous
Chose Amazon EMR
Snowflake is a lot easier to get started with than the other options. Snowflake's data lake building capabilities are far more powerful. Although Amazon EMR isn't our first pick, we've had an excellent experience with EC2 and S3. Because of our current API interfaces, it made …
Verified User
Anonymous
Chose Amazon EMR
1. Amazon EMR was faster than Google BigQuery and this made a difference when the amount of data was really large.
2. Amazon EMR was costlier than Google BigQuery so it was difficult to manage budget.
3. Amazon EMR has excellent integrations with other technologies.
Verified User
Anonymous
Chose Amazon EMR
Amazon EMR (Elastic MapReduce) compares well against Microsoft Azure and Microsoft SQL servers in terms of performance and ease of use. This also means you pay more for the service. Amazon EMR is a great tool for handling large amounts of data. SQL Server would be a better …
Verified User
Anonymous
Chose Amazon EMR
Compared to IBM Analytics Engine, Amazon EMR is a much cheaper option to get the work down. And compared to Alluxio, Amazon EMR is much more user-friendly. The drawback is that amazon EMR would be very costly if the run failed.
Verified User
Anonymous
Chose Amazon EMR
Good choice for startup, open source and cost-effective and saves a lot of setup time.
Run times are reduced to minutes compared to hours on EC2 or other compute servers.
Easy to choose between hadoop or spark based EMR cluster, it can be used in combination with other AWS …
Nick Waters | TrustRadius Reviewer
Nick Waters
Solutions Engineer
Chose Amazon EMR
Amazon EMR (Elastic Map Reduce) compares well against GCP and Azure - but you need to be careful of the costs involved in spinning up such a cluster. It is easy to configure however and it is my preferred platform to deploy our solutions because of its ease of use.
Jonathan Brotto | TrustRadius Reviewer
Jonathan Brotto
SAP Specialist
Chose Amazon EMR
Apache Hadoop required us to do all the leg work and we did not have the resources for that. It was ideal that AWS offers a MapReduce solution as we use it to host various servers. It is one place for all our needs. Very convenient. Apache Hadoop is still a good product but …
Verified User
Anonymous
Chose Amazon EMR
Compared to Databricks, Amazon EMR is a much cheaper option to get the work down. And compared to Amazon ec2, Amazon EMR is a much more powerful tool to get large datasets transformation down in a fairly short amount of time. The drawback is that amazon EMR would be very costly …
Verified User
Anonymous
Chose Amazon EMR
Amazon EMR is faster, cheaper, easier, and enjoyed more by our employees compared to Azure HDInsight. We selected Amazon because we saw an advertisement and wanted to try it out to see how it was. We will continue to use it until it is not around or until we find something that …
Nicolas Costa Ossa | TrustRadius Reviewer
Nicolas Costa Ossa
Director of Customer Operations & Account Management
Chose Amazon EMR
EMR is more suited for developers. Databricks feel more for data science-oriented with its notebooks and customs visualizations. With EMR you can more easily add additional capacity on-damnd on the instance. With others is a more cumbersome process. And then, you can also …
Verified User
Anonymous
Chose Amazon EMR
The alternatives to EMR are mainly hadoop distributions owned by the 3 companies above. I have not used the other distributions so it is difficult to comment, but the general tradeoff is, at the cost of a longer setup time and more infra management, you get more flexible …
Verified User
Anonymous
Chose Amazon EMR
Having one of these enterprise edition license comes at its own costs. But, the flexibility to have the cluster spin up with the workbenches and code snippets on the same is really beneficial. Especially, if one had to move out of EMR and consider an option which reduces the …
Verified User
Anonymous
Chose Amazon EMR
EMR provides dynamic cluster size, lots of documentation, and integration with other Amazon Web Services which are some of the things that Cloudera distribution for Hadoop lacked. Some products are hard to learn but EMR was much easier and helped save time spent on trying to …
SAP Vora

No answer on this topic

Best Alternatives
Amazon EMR (Elastic MapReduce)SAP Vora
Small Businesses

No answers on this topic

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Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 7.1 out of 10
IBM Analytics Engine
IBM Analytics Engine
Score 7.1 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon EMR (Elastic MapReduce)SAP Vora
Likelihood to Recommend
8.0
(0 ratings)
6.0
(0 ratings)
Usability
7.0
(0 ratings)
-
(0 ratings)
Support Rating
9.0
(0 ratings)
-
(0 ratings)
User Testimonials
Amazon EMR (Elastic MapReduce)SAP Vora
Likelihood to Recommend
We are running it to perform preparation which takes a few hours on EC2 to be running on a spark-based EMR cluster to total the preparation inside minutes rather than a few hours. Ease of utilization and capacity to select from either Hadoop or spark. Processing time diminishes from 5-8 hours to 25-30 minutes compared with the Ec2 occurrence and more in a few cases.
José David Rodríguez Gómez | TrustRadius Reviewer
José David Rodríguez Gómez
Director Nacional. Desarrollo de red, procesos y servicio al cliente Posventa
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I spent more than 1 year with SAP Vora, SAP Datahub and SAP Leonardo with ML, iOt. I believe this product has potential but it is not easy to adopt. SAP has to keep in mind how open-source big data technologies are able to deliver quick results. I know SAP is stabilizing and fighting hard against many open source technologies, but it still has a long way to go there.
Dhinesh Kumar Ganeshan,PMP,CSM | TrustRadius Reviewer
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Pros
  • The cluster size of MapReduce is very dynamic and therefore scalability is good for EMR.
  • It also works well with other Amazon Web Services like Amazon Simple Storage Service, which means that data can be taken from those services and written back to them.
  • I tried using the in-house hosting at the university I work in, but there would be a lot of complications with technical support required. For Amazon, the support and documentation was good to solve these problems faster.
Verified User
Anonymous
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  • Modelling with SAP HANA and Hadoop
  • Realtime Analysis using Vora and HANA as a Streaming engine
  • Time series Analysis on large chunks of datasets
  • Machine learning capabilities on Hadoop tables and spark contexts
Dhinesh Kumar Ganeshan,PMP,CSM | TrustRadius Reviewer
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Cons
  • Sometimes bootstrapping certain tools comes with debugging costs. The tools provided by some of the enterprise editions are great compared to EMR.
  • Like some of the enterprise editions EMR does not provide on premises options.
  • No UI client for saving the workbooks or code snippets. Everything has to go through submitting process. Not really convenient for tracking the job as well.
Verified User
Anonymous
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  • Vora 2.0 in on premise scenarios could be improved, as adoption of the cloud is not an easy sell.
  • Kubernetes and Docker integration need to be more seamless and quick to understand. If this is simplified, it will be easy to adopt
  • Data hub orchestration and integrations could be simplified so that quick adoption within SAP BW, ECC, S4 HANa scenarios is possible.
Dhinesh Kumar Ganeshan,PMP,CSM | TrustRadius Reviewer
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Usability
Documentation is quite good and the product is regularly updated, so new features regularly come out. The setup is straightforward enough, especially once you have already established the overall platform infrastructure and the aws-cli APIs are easy enough to use. It would be nice to have some out-of-the-box integrations for checking logs and the Spark UI, rather than relying on know-how and digging through multiple levels to find the informations
Verified User
Anonymous
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No answers on this topic
Support Rating
I give the overall support for Amazon EMR this rating because while the support technicians are very knowledgeable and always able to help, it sometimes takes a very long time to get in contact with one of the support technicians. So overall the support is pretty good for Amazon EMR.
Verified User
Anonymous
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No answers on this topic
Alternatives Considered
Snowflake is a lot easier to get started with than the other options. Snowflake's data lake building capabilities are far more powerful. Although Amazon EMR isn't our first pick, we've had an excellent experience with EC2 and S3. Because of our current API interfaces, it made more sense for us to continue with Hadoop rather than explore other options.
Verified User
Anonymous
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No answers on this topic
Return on Investment
  • It was obviously cheaper and convenient to use as most of our data processing and pipelines are on AWS. It was fast and readily available with a click and that saved a ton of time rather than having to figure out the down time of the cluster if its on premises.
  • It saved time on processing chunks of big data which had to be processed in short period with minimal costs. EMR solved this as the cluster setup time and processing was simple, easy, cheap and fast.
  • It had a negative impact as it was very difficult in submitting the test jobs as it lags a UI to submit spark code snippets.
Verified User
Anonymous
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  • Negative impact would be Poc and RFI will need more time to adopt and decision making gets delayed
  • Positive impact would be it's a great leap from SAP to adopt a Big data technologies and AI within cloud stream. But selling is going to take time.
Dhinesh Kumar Ganeshan,PMP,CSM | TrustRadius Reviewer
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